Real-time Precise Positioning Research Articles

Crowdsourcing RTK: a new GNSS positioning framework for building spatial high-resolution atmospheric maps based on massive vehicle GNSS data

High-quality spatial atmospheric delay correction information is essential for achieving fast integer ambiguity resolution (AR) in precise positioning. However, traditional real-time precise positioning frameworks (i.e., NRTK and PPP-RTK) depend on spatial low-resolution atmospheric delay correction through the expensive and sparsely distributed CORS network. This results in limited public appeal. With the mass production of autonomous driving vehicles, more cost-effective and widespread data sources can be explored to create spatial high-resolution atmospheric maps. In this study, we propose a new GNSS positioning framework that relies on dual base stations, massive vehicle GNSS data, and crowdsourced atmospheric delay correction maps (CAM). The map is easily produced and updated by vehicles equipped with GNSS receivers in a crowd-sourced way. Specifically, the map consists of between-station single-differenced ionospheric and tropospheric delays. We introduce the whole framework of CAM initialization for individual vehicles, on-cloud CAM maintenance, and CAM-augmented user-end positioning. The map data are collected and preprocessed in vehicles. Then, the crowdsourced data are uploaded to a cloud server. The massive data from multiple vehicles are merged in the cloud to update the CAM in time. Finally, the CAM will augment the user positioning performance. This framework forms a beneficial cycle where the CAM’s spatial resolution and the user positioning performance mutually improve each other. We validate the performance of the proposed framework in real-world experiments and the applied potency at different spatial scales. We highlight that this framework is a reliable and practical positioning solution that meets the requirements of ubiquitous high-precision positioning.

A novel mode of INS-aided BDS real-time high-rate and precise kinematic relative positioning between two moving platforms

ABSTRACT For kinematic relative positioning users between two moving platforms, limited communication bandwidth and computation ability usually cannot support real-time transmission of high-rate (≥10 Hz) BeiDou Navigation Satellite System (BDS) data. The performance of Ambiguity Resolution (AR) is also a major challenge in signal blocked and loss of lock environments. Based on BDS and Inertial Navigation System (INS) data, we develop a novel mode of INS-aided BDS kinematic relative positioning between two moving platforms, aiming to realize real-time, high-rate and precise positioning with low-cost communication modules in challenge environments. To achieve this goal, the INS-aided high-rate relative kinematic positioning and INS-aided BDS AR re-initialization methods are proposed. In this mode, the baseline bias caused by the different position datum is first defined and resolved. Then, high-rate INS data are assisted to obtain kinematic relative position when real-time kinematic positioning results are unavailable within 1 second. Once the BDS data are available, the predicted relative position is used as additional constraint to facilitate AR re-initialization and improve the kinematic positioning performance. The performance of these methods is discussed in a set of experiments with 1 Hz BDS data and 100 Hz INS data, and compared with the conventional method by sending raw BDS/INS measurements. The results show that the proposed methods can achieve an accuracy of about 5 cm for the INS-aided 100 Hz relative positioning in baseline components and lengths, which is equal to the conventional method, but the transmitted data have been sharply reduced by an average of nearly 80%. With the assistance of INS-predicted baseline constraint, the relative positioning performance has been further improved. The accuracy of baseline length errors is less than 4 cm, and the AR fixing rates keep larger than 95% during the experiment, while the wrongly fixed rates are reduced to less than 0.5%.

Visible CCD Camera-Guided Photoacoustic Imaging System for Precise Navigation during Functional Rat Brain Imaging

In photoacoustic (PA) imaging, tissue absorbs specific wavelengths of light. The absorbed energy results in thermal expansion that generates ultrasound waves that are reconstructed into images. Existing commercial PA imaging systems for preclinical brain imaging are limited by imprecise positioning capabilities and inflexible user interfaces. We introduce a new visible charge-coupled device (CCD) camera-guided photoacoustic imaging (ViCPAI) system that integrates an ultrasound (US) transducer and a data acquisition platform with a CCD camera for positioning. The CCD camera accurately positions the US probe at the measurement location. The programmable MATLAB-based platform has an intuitive user interface. In vitro carbon fiber and in vivo animal experiments were performed to investigate the precise positioning and imaging capabilities of the ViCPAI system. We demonstrated real-time capturing of bilateral cerebral hemodynamic changes during (1) forelimb electrical stimulation under normal conditions, (2) forelimb stimulation after right brain focal photothrombotic ischemia (PTI) stroke, and (3) progression of KCl-induced cortical spreading depression (CSD). The ViCPAI system accurately located target areas and achieved reproducible positioning, which is crucial in animal and clinical experiments. In animal experiments, the ViCPAI system was used to investigate bilateral cerebral cortex responses to left forelimb electrical stimulation before and after stroke, showing that the CBV and SO2 in the right primary somatosensory cortex of the forelimb (S1FL) region were significantly changed by left forelimb electrical stimulation before stroke. No CBV or SO2 changes were observed in the bilateral cortex in the S1FL area in response to left forelimb electrical stimulation after stroke. While monitoring CSD progression, the ViCPAI system accurately locates the S1FL area and returns to the same position after the probe moves, demonstrating reproducible positioning and reducing positioning errors. The ViCPAI system utilizes the real-time precise positioning capability of CCD cameras to overcome various challenges in preclinical and clinical studies.

An efficient strategy for multi-GNSS real-time clock estimation based on the undifferenced method

Precise satellite clock product is an indispensable prerequisite for the real-time precise positioning service. To meet the requirement of numerous time-critical applications, real-time satellite clock corrections need to be broadcast to users with an update rate of 5 s or higher. With the rapid development of global navigation satellite systems (GNSS) over the past decades, abundant GNSS tracking stations and modern constellations have emerged, and the computation for multi-GNSS real-time clock estimation has become rather time-consuming. In this contribution, an efficient strategy is proposed to achieve high processing efficiency for multi-GNSS real-time clock estimation, wherein undifferenced method based on sequential least square is adopted. In the proposed strategy, parallel data processing and high-performance matrix operations are introduced to accelerate the processing of multi-GNSS clock estimation. The former is based on OpenMP (Open Multi-Processing), while the latter is achieved by the implementation of the Schur complement and the open-source library OpenBLAS. Multi-GNSS observations from 85 globally distributed tracking stations are employed for the generation of real-time precise clock products. The average elapsed time per epoch with the proposed strategy is 0.35, 0.68, and 2.30 s for GPS-only, dual-system, and quad-system solutions, respectively. Compared to the traditional serial strategy, the computation efficiency is significantly improved by 76.0%, 77.3%, and 77.7%, respectively. The accuracy of the estimated clocks is evaluated with respect to IGS final GPS clock products and GFZ final multi-GNSS clock products (GBM0MGXRAP), and multi-GNSS real-time precise point positioning (PPP) experiments are further carried out. All the results indicate that the proposed strategy is efficient, accurate, and can promise high-rate multi-GNSS real-time clock estimation.

A Kalman filter-based online fractional cycle bias determination method for real-time ambiguity-fixing GPS satellite clock estimation

Integer ambiguity resolution (IAR) is one of the most powerful methods to improve the precision and the convergence of estimating real-time satellite clocks, which is an indispensable prerequisite to support the real-time precise point position (PPP) service. In this study, a Kalman filter-based online fractional cycle bias (FCB) determination method is proposed to facilitate the real-time IAR for satellite clock estimation. A real-time recursive algorithm for smoothing the average float wide-lane (WL) ambiguity is developed to mitigate the impact of pseudorange noise. Quality control procedures are established throughout the entire FCB filter process to remove low-quality observations and mitigate the impact of incorrect integer ambiguities. This method is designed as an embedded module in the clock estimation procedure to fix both integer WL and narrow-lane (NL) ambiguities in an epoch-by-epoch way for recovering the integer property of the undifferenced ionosphere-free (IF) ambiguities in real-time. The performance of the FCB filter and the ambiguity-fixing clock estimation is validated with a GPS network from the international GNSS service (IGS). Experiments show that the WL and NL FCB estimation accuracy reaches 0.004 cycles and 0.080 cycles for GPS satellites. The WL and NL residuals fit the normal distribution well after several minutes and 1.5 h, respectively, making the ambiguity-fixing clocks converge rapidly in about two hours. The online FCB filter method improves real-time ambiguity-fixing clock estimation accuracy significantly. Compared to the ambiguity-float solution, the STD of the ambiguity-fixing real-time satellite clocks is averagely improved by 31.0 % to 0.040 ns with the ultra-rapid orbits. The ambiguity-fixing satellite clocks can be applied in the real-time kinematic PPP ambiguity resolution, and the positioning accuracy is improved by 24.1 % to 51.7 % compared to that of using the ambiguity-float clock products.

Assessment of Real-Time PPP with Trimble RTX correction service for real-time dynamic displacement monitoring based on high-rate GNSS observations

Real-time displacement monitoring of earth crust and engineering structures with the Global Navigation Satellite System (GNSS) is highly important for detecting and preventing the damage and possible loss of life during natural phenomena. Nowadays, the Real-Time Kinematic Precise Point Positioning (RT-PPP) method using a stand-alone GNSS receiver can provide fast and accurate dynamic displacement. Trimble Real-Time Extended (RTX) technology enables real-time precise positioning with cm-level accuracy in a short convergence time. The present study investigates, for the first time, the dynamic displacement detection performance of RT-PPP based on CenterPoint RTX correction service for early warning systems and rapid risk assessment. To evaluate the performance of Trimble RTX technology, a series of shake table experiments were conducted and harmonic oscillations with different frequencies and amplitudes were generated. Trimble RTX solutions were obtained at 20 Hz sampling rate and compared with Linear Variable Differential Transformer (LVDT) data, considered as reference, in both frequency and time domains. Results show that Trimble RTX technology can accurately detect the frequency of harmonic motions, whose amplitudes are slightly different from LVDT values because of GNSS inherent noise. The average of Root Mean Square Error (RMSE) values obtained from the differences between LVDT and filtered RTX-derived time series for all events is 3.6 mm. These results indicated that the CenterPoint RTX technology could be employed for real-time and near-real-time applications to monitor structural and earthquake-induced motions accurately.

An improved weighting strategy for tropospheric delay estimation with real-time single-frequency precise positioning

An improved weighting strategy for tropospheric delay estimation with real-time single-frequency precise positioning

Research and Application of Haar Wavelet Transformation in Train Positioning

With the continuous increase of the urban population, urban traffic problems have become increasingly prominent. The subway and light rail have the characteristics of large passenger volume and low pollution, which are the preferred solutions to solve the traffic problems in large and medium cities. Due to the high density of rail transit trains, the close distance between stations, and the high safety requirements, the real-time and accurate determination of the train's position on the line is the premise to ensure safety, maximize efficiency, and provide the best service. How to accurately detect the speed and position of the train to control its the operation is the core content of the rail transit system. Therefore, the in-depth study of train positioning methods has great and far-reaching significance for promoting the research of train operation control system and the development of rail transit system. It has become a research hotspot to rely on computer technology and image recognition technology to realize precise positioning of trains. In order to realize the real-time precise positioning of the train, this paper proposes a train positioning method based on Haar wavelet transform. First, the samples are obtained by the method of video acquisition, and the video images are initially processed by binarization. Second, the image is compressed, denoised, and enhanced by Haar wavelet transform, and the train number is determined. Finally, the orbital electronic map and satellite assistance are used to determine the position of the train and realize the train positioning. The simulation experiments show that the image acquired by Haar wavelet transform can accurately identify the train and track. Based on the satellite aid of the orbital electronic map, the train positioning can be accurately realized, and the proposed Haar wavelet transform is proposed and has good positioning accuracy.

Real-Time Modeling of Regional Tropospheric Delay Based on Multicore Support Vector Machine

Real-time modeling of regional troposphere has attracted considerable research attention in the current GNSS field, and its modeling products play an important role in global navigation satellite system (GNSS) real-time precise positioning and real-time inversion of atmospheric water vapor. Multicore support vector machine (MS) based on genetic optimization algorithm, single-core support vector machine (SVM), four-parameter method (FP), neural network method (BP), and root mean square fusion method (SUM) are used for real-time and final zenith tropospheric delay (ZTD) modeling of Hong Kong CORS network in this study. Real-time ZTD modeling experiment results for five consecutive days showed that the average deviation (bias) and root mean square (RMS) of FP, BP, SVM, and SUM reduced by 48.25%, 54.46%, 41.82%, and 51.82% and 43.16%, 48.46%, 30.09%, and 33.86%, respectively, compared with MS. The final ZTD modeling experiment results showed that the bias and RMS of FP, BP, SVM, and SUM reduced by 3.80%, 49.78%, 25.71%, and 49.35% and 43.16%, 48.46%, 30.09%, and 33.86%, respectively, compared with MS. Accuracy of the five methods generally reaches millimeter level in most of the time periods. MS demonstrates higher precision and stability in the modeling of stations with an elevation at the average level of the survey area and higher elevation than that of other models. MS, SVM, and SUM exhibit higher precision and stability in the modeling of the station with an elevation at the average level of the survey area than FP. Meanwhile, real-time modeling error distribution of the five methods is significantly better than the final modeling. Standard deviation and average real-time modeling improved by 43.19% and 24.04%, respectively.

Approaching Global Instantaneous Precise Positioning with the Dual- and Triple-Frequency Multi-GNSS Decoupled Clock Model

Precise Point Positioning (PPP), as a global precise positioning technique, suffers from relatively long convergence times, hindering its ability to be the default precise positioning technique. Reducing the PPP convergence time is a must to reach global precise positions, and doing so in a few minutes to seconds can be achieved thanks to the additional frequencies that are being broadcast by the modernized GNSS constellations. Due to discrepancies in the number of signals broadcast by each satellite/constellation, it is necessary to have a model that can process a mix of signals, depending on availability, and perform ambiguity resolution (AR), a technique that proved necessary for rapid convergence. This manuscript does so by expanding the uncombined Decoupled Clock Model to process and fix ambiguities on up to three frequencies depending on availability for GPS, Galileo, and BeiDou. GLONASS is included as well, without carrier-phase ambiguity fixing. Results show the possibility of consistent quasi-instantaneous global precise positioning through an assessment of the algorithm on a network of global stations, as the 67th percentile solution converges below 10 cm horizontal error within 2 min, compared to 8 min with a triple-frequency solution, showing the importance of having a flexible PPP-AR model frequency-wise. In terms of individual datasets, 14% of datasets converge instantaneously when mixing dual- and triple-frequency measurements, compared to just 0.1% in that of dual-frequency mode without ambiguity resolution. Two kinematic car datasets were also processed, and it was shown that instantaneous centimetre-level positioning with a moving receiver is possible. These results are promising as they only rely on ultra-rapid global satellite products, allowing for instantaneous real-time precise positioning without the need for any local infrastructure or prior knowledge of the receiver’s environment.

A fast RFID image matching algorithm for multi-tag identification and distribution optimization

We propose an improved image matching algorithm that combines the minimum feature value algorithm to extract feature points and the direction gradient histogram to calculate the description vector. This algorithm is oriented to RFID multi-tag identification and distribution optimization in the actual scenario, and the traditional SURF algorithm has the problems of low matching accuracy and high complexity in multi-tag matching. This algorithm effectively improves the positioning accuracy of the RFID multi-tag positioning system. The experimental results show that the matching success rate of the improved algorithm in this paper is 87.4%, which is 50% higher than the SURF algorithm. Not only the matching accuracy is greatly improved, but the running speed is also increased by 48%. The algorithm in this paper has high matching accuracy and real-time performance.It provides an effective way for RFID multi-tag real-time fast matching and precise positioning.

Best integer equivariant estimation: performance analysis using real data collected by low-cost, single- and dual-frequency, multi-GNSS receivers for short- to long-baseline RTK positioning

The key to precise global navigation satellite system (GNSS) positioning is carrier phase integer ambiguity resolution with a high success rate. On the other hand when the success rate is too low, the user will normally prefer the float solution. The alternative can be to use the best integer equivariant (BIE) estimator, since it is optimal in the minimum mean squared error (MMSE) sense. Low-cost receiver real-time kinematic precise positioning has become possible through the many signals that can be obtained by combining several GNSSs, such as BDS, Galileo, QZSS and GPS. In this contribution, we will use both simulations and such low-cost multi-GNSS data to compare the performance of the BIE and integer least squares (ILS) estimator, based on full ambiguity resolution. The GNSS data are evaluated in Dunedin, New Zealand, with a short- (670 m) and long-baseline (112.9 km) where the relative atmospheric delays can be neglected and need to be estimated, respectively. We compare the BIE and ILS results by using both single-frequency and dual-frequency (DF) low-cost and survey-grade receivers and antennas. We demonstrate, for the first time, the distributional properties of BIE positioning, where it will be shown that a ‘star-like’ pattern reveals itself once the model gets stronger and the ILS success rate increases. It will further be shown that the DF low-cost receivers give a very good positioning performance, but still not yet competitive to the survey-grade counterparts for the long-baseline. We will also demonstrate that the positioning performance of the BIE estimator will always equal or be better than that of the float solutions. It will finally be shown that BIE will always be better in the MMSE sense than the ILS solution when the success rate is at low to medium levels, whereas for high success rates we get a similar performance to ILS.

Models, methods and assessment of four-frequency carrier ambiguity resolution for BeiDou-3 observations

One of the most significant advantages of multiple frequencies is that it can improve the success rate of ambiguity resolution, such as the three-frequency carrier ambiguity resolution (TCAR) method. So far, the global BeiDou-3 navigation satellite system already provides four frequencies. Hence, we systematically study the models and methods of four-frequency carrier ambiguity resolution (FCAR) by using real BeiDou-3 data. First, the models of four-frequency linear combinations are given, and the optimal linear combinations are found out based on certain optimal criteria. Second, two typical methods, including geometry-free and geometry-based methods, are studied. In the end, the real BeiDou-3 data are used to evaluate the performance of the FCAR method, where two strategies, i.e., single-epoch and multi-epoch solutions, are both applied. The results indicate that the FCAR method can offer more high-quality virtual signals in quantity and quality than the TCAR method. By using the real BeiDou-3 data with different lengths ranging from 4.9 m to 61.6 km, three high-quality and independent signals can fix the ambiguities instantaneously with an approximately 100% success rate. Then the fourth independent signal can be fixed with high efficiency and success rate. Therefore, the FCAR method is promising in large-scale real-time precise positioning, where the successful ambiguity resolution may take tens of minutes to hours.

Real-time GNSS precise positioning: RTKLIB for ROS

The global navigation satellite system (GNSS) constitutes an effective and affordable solution to the outdoor positioning problem. When combined with precise positioning techniques, such as the real time kinematic (RTK), centimeter-level positioning accuracy becomes a reality. Such performance is suitable for a whole new range of demanding applications, including high-accuracy field robotics operations. The RTKRCV, part of the RTKLIB package, is one of the most popular open-source solutions for real-time GNSS precise positioning. Yet the lack of integration with the robot operating system (ROS), constitutes a limitation on its adoption by the robotics community. This article addresses this limitation, reporting a new implementation which brings the RTKRCV capabilities into ROS. New features, including ROS publishing and control over a ROS service, were introduced seamlessly, to ensure full compatibility with all original options. Additionally, a new observation synchronization scheme improves solution consistency, particularly relevant for the moving-baseline positioning mode. Real application examples are presented to demonstrate the advantages of our rtkrcv_ros package. For community benefit, the software was released as an open-source package.

Performance of real-time undifferenced precise positioning assisted by remote IGS multi-GNSS stations

The heavy reliance of real-time precise point positioning (RTPPP) on external satellite clock products may lead to discontinuity or even failure in time-critical applications. We present an alternative approach of real-time undifferenced precise positioning (RUP) that, by combining satellite clock estimation and precise point positioning based on the extended Kalman filter, is independent of external satellite clock corrections. The approach is evaluated in simulated real time with the assistance of a variable number of IGS multi-GNSS stations located between 1359.7 and 4852.5 km from the users. The results show that even with a single auxiliary IGS station, RUP is still feasible and able to retain centimeter-level positioning accuracy. Typically, with three auxiliary IGS stations about 2000–3000 km away, an accuracy of about 2 cm in the horizontal and 5 cm in the vertical can be achieved. The performance of RUP is comparable to that of PPP using 5-s satellite clock products and notably exhibits superior short-term precision in dealing with high-rate (1 Hz) GPS/GLONASS observations. The addition of GLONASS observations reduces the convergence time by 56.9% and improves the 3-D position accuracy by 31.8% while increasing the processing latency by a factor of about 1.6. Employing three IGS stations over 2400 km away from the epicenter, RUP is applied for the rapid determination of coseismic displacements and waveforms for the 2016 Kaikoura earthquake, yielding highly consistent results compared to those obtained from post-processed PPP in the global reference frame. We also explore its potential in facilitating real-time online services in terms of real-time precise positioning, zenith tropospheric delay retrieving, and satellite clock estimation.

GNSS: A revolution for precise geopositioning

Abstract Global Navigation Satellite Systems (GNSS) were not initially designed to be used for precise scientific applications. However, a smart signal processing can provide a satellite–receiver range measurement with millimeter accuracy. If the differential technique has become an essential method, the PPP mode is today an increasingly popular alternative. But, whatever the approach, GNSS have revolutionized the realization of space and time frames and the many applications requiring post-processed or real-time precise positioning.

LEO enhanced Global Navigation Satellite System (LeGNSS) for real-time precise positioning services

Global Navigation Satellite System (GNSS) has been widely used in many geosciences areas with its Positioning, Navigation and Timing (PNT) service. However, GNSS still has its own bottleneck, such as the long initialization period of Precise Point Positioning (PPP) without dense reference network. Recently, the concept of PNTRC (Positioning, Navigation, Timing, Remote sensing and Communication) has been put forward, where Low Earth Orbit (LEO) satellite constellations are recruited to fulfill diverse missions. In navigation aspect, a number of selected LEO satellites can be equipped with a transmitter to transmit similar navigation signals to ground users, so that they can serve as GNSS satellites but with much faster geometric change to enhance GNSS capability, which is named as LEO constellation enhanced GNSS (LeGNSS). As a result, the initialization time of PPP is expected to be shortened to the level of a few minutes or even seconds depending on the number of the LEO satellites involved. In this article, we simulate all the relevant data from June 8th to 14th, 2014 and investigate the feasibility of LeGNSS with the concentration on the key issues in the whole data processing for providing real-time PPP service based on a system configuration with fourteen satellites of BeiDou Navigation Satellite System (BDS), twenty-four satellites of the Global Positioning System (GPS), and sixty-six satellites of the Iridium satellite constellations. At the server-end, Precise Orbit Determination (POD) and Precise Clock Estimation (PCE) with various operational modes are investigated using simulated observations. It is found out that GNSS POD with partial LEO satellites is the most practical mode of LeGNSS operation. At the user-end, the Geometry Dilution Of Precision (GDOP) and Signal-In-Space Ranging Error (SISRE) are calculated and assessed for different positioning schemes in order to demonstrate the performance of LeGNSS. Centimeter level SISRE can be achieved for LeGNSS.

Performance Analysis of GPS/BDS Dual/Triple-Frequency Network RTK in Urban Areas: A Case Study in Hong Kong.

Network Real Time Kinematic (NRTK) positioning with instantaneous ambiguity resolution (AR) is currently one of the most popular techniques for real-time precise positioning using Global Navigation Satellite Systems (GNSS) carrier phase observations. Although NRTK has been successfully applied in many fields in surveying and navigation, the initialization speed, accuracy, and ambiguity successfully fixed rate of NRTK in urban areas (Hong Kong, for instance) would be significantly affected by blocked satellite signals. To address these problems and analyze the performance of GPS/BDS dual/triple-frequency NRTK in urban areas, we developed a new Hong Kong GNSS Network RTK Service Platform. Based on this platform, the performance of NRTK in urban areas was examined through a series of experiments. The results showed that: (1) The initialization time of the NRTK varied with the number of the visible satellite and the quality of the observation. (2) Centimeter-level NRTK service could be provided for users over Hong Kong using the Hong Kong GNSS Network RTK Service Platform. (3) In urban areas, GPS/BDS NRTK services for static, walking, and driving users significantly improved the ambiguity successfully fixed rate of the NRTK service when compared with that using the GPS signal alone. The NRTK ambiguity successfully fixed rate in Hong Kong was better than 99% in good environment. In typical urban environment, the RTK ambiguity successfully fixed rate with GPS/BDS was 33.4–72.4%, which was about 12.7–32.4% with GPS only. (4) BDS triple-frequency observation improved the initialization speed and positioning accuracy of RTK in Hong Kong.

Evaluation of a regional real-time precise positioning system based on GPS/BeiDou observations in Australia

The performance of real-time (RT) precise positioning can be improved by utilizing observations from multiple Global Navigation Satellite Systems (GNSS) instead of one particular system. Since the end of 2012, BeiDou, independently established by China, began to provide operational services for users in the Asia-Pacific regions. In this study, a regional RT precise positioning system is developed to evaluate the performance of GPS/BeiDou observations in Australia in providing high precision positioning services for users. Fixing three hourly updated satellite orbits, RT correction messages are generated and broadcasted by processing RT observation/navigation data streams from the national network of GNSS Continuously Operating Reference Stations in Australia (AUSCORS) at the server side. At the user side, RT PPP is realized by processing RT data streams and the RT correction messages received. RT clock offsets, for which the accuracy reached 0.07 and 0.28 ns for GPS and BeiDou, respectively, can be determined. Based on these corrections, an accuracy of 12.2, 30.0 and 45.6 cm in the North, East and Up directions was achieved for the BeiDou-only solution after 30 min while the GPS-only solution reached 5.1, 15.3 and 15.5 cm for the same components at the same time. A further improvement of 43.7, 36.9 and 45.0 percent in the three directions, respectively, was achieved for the combined GPS/BeiDou solution. After the initialization process, the North, East and Up positioning accuracies were 5.2, 8.1 and 17.8 cm, respectively, for the BeiDou-only solution, while 1.5, 3.0, and 4.7 cm for the GPS-only solution. However, we only noticed a 20.9% improvement in the East direction was obtained for the GPS/BeiDou solution, while no improvements in the other directions were detected. It is expected that such improvements may become bigger with the increasing accuracy of the BeiDou-only solution.

An investigation into the performance of real-time GPS+GLONASS Precise Point Positioning (PPP) in New Zealand

Abstract This paper presents an investigation into the performance of real-time Global Navigation Satellite Systems (GNSS) Precise Point Positioning (PPP) in New Zealand. The motivation of the research is to evaluate the feasibility of using PPP technique and a satellite based augmentation system such as the Japanese Quasi-Zenith Satellite System (QZSS) to deliver a real-time precise positioning solution in support of a nation-wide high accuracy GNSS positioning coverage in New Zealand. Two IGS real-time correction streams are evaluated alongside with the PPP correction messages transmitted by the QZSS satellite known as MDC1. MDC1 corrections stream is generated by Japan Aerospace Exploration Agency (JAXA) using the Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) software and are currently transmitted in test mode by the QZSS satellite. The IGS real-time streams are the CLK9B real-time corrections stream generated by the French Centre National D’études Spatiales (CNES) using the PPP-Wizard software, and the CLK81 real-time corrections stream produced by GMV using their MagicGNSS software. GNSS data is collected from six New Zealand CORS stations operated by Land Information New Zealand (LINZ) over a one-week period in 2015. GPS and GLONASS measurements are processed in a real-time PPP mode using the satellite orbit and clock corrections from the real-time streams. The results show that positioning accuracies of 6 cm in horizontal component and 15 cm in vertical component can be achieved in real-time PPP. The real-time GPS+GLONASS PPP solution required 30 minutes to converge to within 10 cm horizontal positioning accuracy.